dtourolle
d8304d7c82
The noise model takes the best source the frame has: the body's measured table (the Canon EOS 6D's, from the library), the DNG's NoiseProfile, or the frame itself — read, row and column noise from its masked border, and only the shot gain estimated, from the quietest flat patches. Checked on 130 6D frames, the estimate is within 10 % from ISO 1000 up; the network loses under 0.3 dB for a sigma off by 15-20 %, so every Bayer body is eligible. Tiles of 1408 keep their central 1024 behind a 192-photosite halo, past the 185-photosite receptive field, and the frame is extended by reflection, which keeps every photosite's colour; a pattern that starts on another colour is read from one photosite up or left so the network sees RGGB, and nothing is cropped. The tests run every Bayer phase, tiled against whole, with a stand-in network of known reach. The model ships as models/denoise/mosaic-1408.onnx (LFS), trained in darkroom-denoise on the maintainer's own photographs, GPL like the code. denoise_raw runs a file end to end: on a 6D frame at ISO 8000 the result matches the training repository's own path to 2.5e-4 at worst, and takes 3.1 s on TensorRT fp16 (75 dB from f32) or 14.4 s on the CPU.
33 lines
1.0 KiB
TOML
33 lines
1.0 KiB
TOML
[package]
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name = "dr-denoise"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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license.workspace = true
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[dependencies]
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dr-decode.workspace = true
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serde = { workspace = true }
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serde_norway.workspace = true
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thiserror.workspace = true
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log.workspace = true
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# The network runs under the inference engine like every other model
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# (docs/dev/inference.md): `ort` is the API, the engine picks the rung.
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# Optional so the noise model and the tiling test without a runtime.
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ort = { workspace = true, optional = true }
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dr-inference-engine = { workspace = true, optional = true }
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ndarray = { workspace = true, optional = true }
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[features]
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default = ["onnx"]
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onnx = ["dep:ort", "dep:dr-inference-engine", "dep:ndarray"]
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# A real ONNX Runtime from disk rather than tract alone, as the app links it.
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native = ["onnx", "dr-inference-engine/native"]
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[dev-dependencies]
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# The example repairs hot photosites with the app's own pass, as develop will.
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dr-gpu.workspace = true
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pollster.workspace = true
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env_logger.workspace = true
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